Biparametric Information Measures-Based TODIM Technique for Interval-Valued Intuitionistic Fuzzy Environment

Abstract

This paper presents a novel decision-making approach, known as TODIM, in interval-valued intuitionistic fuzzy (IVIF) environment, which determines an optimal alternative by considering psychological behaviours of decision makers under risk. In recent years, TODIM technique has been developed by several authors in various discipline, but they are not able to deal with interdependent characteristics among the criteria. In the present manuscript, the TODIM technique is discussed on the basis of Shapley values under IVIFSs for some situations where elements in a set are correlated. To determine the Shapley values, an entropy measure for IVIFSs is proposed and compared with existing entropy measures. A similarity measure for IVIFSs is introduced to measure the dominance degree of each alternative over others. Mathematical illustration is demonstrated to show the competency of the proposed similarity measure. To deal with interdependent or interactive problem, we have developed Shapley-weighted similarity measure for IVIFSs based on proposed similarity measure and Shapley function. Application of proposed Shapley-weighted similarity measure is presented in pattern recognition problem and then compared with existing measures. Finally, an example of plant location selection is taken to demonstrate the validity and benefit of the proposed technique.